The Cryosphere
The Cryosphere
TC
Articles | Volume 16, issue 11
Articles | Volume 16, issue 11
https://doi.org/10.5194/tc-16-4593-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-16-4593-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 16, issue 11
Research article
 | 
03 Nov 2022
Research article |  | 03 Nov 2022

A random forest model to assess snow instability from simulated snow stratigraphy

Stephanie Mayer, Alec van Herwijnen, Frank Techel, and Jürg Schweizer

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Latest update: 13 Dec 2024
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Short summary
Information on snow instability is crucial for avalanche forecasting. We introduce a novel machine-learning-based method to assess snow instability from snow stratigraphy simulated with the snow cover model SNOWPACK. To develop the model, we compared observed and simulated snow profiles. Our model provides a probability of instability for every layer of a simulated snow profile, which allows detection of the weakest layer and assessment of its degree of instability with one single index.
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